Numerical Algorithms Methods for Computer Vision Machine Learning and 无水印pdf

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Numerical Algorithms Methods for Computer Vision Machine Learning and Graphics 英文无水印pdf pdf所有页面使用FoxitReader和PDF-XChangeViewer测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 本资源转载自网络，如有侵权，请联系上传者或csdn删除
Numerical Algorithms Numerical gorithms Methods for Computer vision, Machine learning, and graphics Justin Solomon (CRC) CRC Press Taylor francis Group Boca talon London New york CRC Press is an imprint of the aylor FranIcis Group, an informa business ANA K PETERS BOOK CRC Press Taylor Francis Group 6000 Broken Sound Parkway NW, Suite 300 Boca raton Fl 33487-2742 o 2015 by Taylor Francis Group, LLC CRC Press is an imprint of Taylor Francis group, an Informa business No claim to original U.S. Government works Version date: 20150105 International Standard Book Number-13: 978-1-4822-5189-0(eBook-PDF This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have beer made to publish reliable data and information, but the author and publisher cannot assume responsibility for the valid ity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or uti- lized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopy ing, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers Forpermissiontophotocopyorusematerialelectronicallyfromthisworkpleaseaccesswww.copyright.com(http:// www.copyright.com/)orcontacttheCopyrightClearanceCenterInc.(ccc),222RosewooddrIve,Danvers,Ma01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe Visit the Taylor francis Web site at http://www.taylorandfrancis.com and the crc press Web site at http://www.crcpress.com In memory of clifford Nass (19582013) Contents PREFACE ACKNOWLEDGMENTS XIX SECTION I Preliminaries ChaPTer 1. Mathematics Review 1. 1 PRELIMINARIES: NUMBERS AND SETS 1.2 VECTOR SPACES 1.2. 1 Defining Vector Spaces 1. 2.2 Span, Lincar Indcpcndencc, and bascs 1.2.3 Our Focus: RTL 1.3 LINEARITY 1.3.1 Matrices 1.3.2 Scalars, Vectors and matrices 12 1.3.3 Matrix Storage and Multiplication Methods 13 1.3.4 Model problem: ar= 1. 4 NON-LINEARITY: DIFFERENTIAL CALCULUS 15 1. 4.1 Differentiation in One Variable 1.4.2 Differentiation in Multiple variables 17 1.4.3 Optimization 20 1.5 EXERCISES 23 CHAPTER 2 Numerics and Error Analysis 27 2.1 STORING NUMBERS WITH FRACTIONAL PARTS 27 2.1.1 Fixed-Point Representations 2.1. 2 Floating-Point Representations 29 2.1.3 More Exotic Options 2.2 UNDERSTANDING ERROR 32 2.2.1 Classifying Error 2.2.2 Conditioning, Stability, and Accuracy 2.3 PRACTICAL ASPECTS 36 2.3.1 Computing Vcctor Norms 37 i■ Contents 2.3.2 Larger-Scale Example: Summation 38 2.4 EXERCISES 3 SECTION II Linear algebra CHAPTER 3 Linear Systems and the LU Decomposition 47 3.1 SOLVABILITY OF LINEAR SYSTEMS 47 3.2 AD-HOC SOLUTION STRATEGIES 9 3.3 ENCODING ROW OPERATIONS 51 3.3.1 Permutation 51 3.3.2 Row Scaling 52 3.3.3 Elimination 52 3.4 GAUSSIAN ELIMINATION 54 3.4.1 Forward-Substitlltion 55 3.4.2 Back-Substitution 3.4.3 Analysis of Gaussian Elimination 56 3.5 LU FACTORIZATION 58 3.5.1 Constructing thc Factorization 3.5.2 Using the factorization 3.53 Implementing 61 3.6 EXERCISES 61 CHAPTER 4 Designing and analyzing linear Systems 65 4.1 SOLUTION OF SQUARE SYSTEMS 4.1.1 Regression 4.1.2 Least-Squares 4.1.3 Tikhonov RegularizatiOn 4.1.4 Image Alignment 71 4.1.5 Deconⅴ olution 4.1.6 Harmonic Parameterization 74 4.2 SPECIAL PROPERTIES OF LINEAR SYSTEMS 75 4.2.1 Positive Definite Matrices and the Cholesky Factorization 4.2.2 Sparsity 4.2.3 Additional Special Structures 4.3 SENSITIVITY ANALYSIS 81 4.3.1 Matrix and Vector norms 81 4.3.2 Condition numbers 4.4 EXERCISES 86 【实例截图】
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